spectre retweeted
An organized disinformation campaign about Ukraine's Starlink access has dropped on Twitter.
The richest man in the world needs bots and paid trolls for validation.
>the agents were communicating before the cut (unrealistic)
>meltdown isn't like what the name implies a cpu temp change hack it is a cache time speculation hack
>already solved by aws
>LLMS being able to recall spectre /meltdown a bug known since 2018 is not impressive
spectre retweeted
brother, the main vulnerability in question was /discovered/ and /patched/ thanks to AI. like, this hasnt even been the largest set of cyber incidents since i started following them.
that said, of course part of the attacks were ai driven. people use the available tools. that was not my point tho?
Replying to @lumpenspace
what a shocking level of delusion you must live under to believe that the cyber events of this week are not ai driven. in a few years you’ll be saying, “these vulnerabilities in the human body have always been there, ai is just exposing the underlying weakness of flesh.”
i will explain to this plep
the php stuff was discovered in august it was the hacker who was too hasty to release it 14 hours before the update and the php foundation too slow to fix it (they wanted to fix the entire class of bugs)
these are not attacks this are disclosed cves
spectre retweeted
今まで海外で海賊版があまり非難されない理由がマジでわからなかったんだが
EAの経営陣が自分達の報酬数百万$上乗せしつつ従業員の給与は22年以来最低、更にビッグタイトル持ちのスタジオ閉鎖させるこの件見て少しだけ理解した
海外は経営層がユーザーやクリエイターに敵対的過ぎる
【速報】EAが「BioWareを閉鎖」し、『Mass Effect』最新作も開発中止。歴史あるRPGスタジオに、突然の幕切れ
automaton-media.com/articles…
spectre retweeted
Vibe coding has created a security epidemic.
(And I’m partially to blame)
When we launched GitHub Copilot in 2021, it combined GPT’s code generation with GitHub’s data. It could auto-complete a function from just its docstring.
5 years on, AI coding agents are orders of magnitude more powerful. Now a single prompt can send Astra or Fable off to write 1000s of lines of code without human intervention.
These models are trained on public source code, which doesn’t follow secure coding best practices. They generate more vulnerabilities than seasoned professionals would. Almost half of AI-written code fails basic security tests.
If you're shipping AI-written code, here's what I'd do:
1. Embed secure coding in your agents.
Don't leave it to each developer to remember. Write your secure coding requirements into the prompts every coding agent in your org runs with. Then review AI-written code with the same rigor as human-written code.
2. Closely scrutinize access controls.
AI is getting better at avoiding textbook bugs. Where it still struggles is your business logic: who should see what, and who can do what.
We recently tested an app where users upload documents for AI analysis. Nobody told the AI the documents should be private, so every user could see everyone else's…
3. Runtime testing at the speed you ship.
If agents write code around the clock, an annual pentest is not enough. Security testing has to be continuous and automated.
4. Assume attackers are already deploying autonomous attacks.
They won't tell you what they find. You need to find it first.
i don't understand these crowds honestly they wanna get scammed so bad
the current state of AI
NS proof isn't actually NS it found a loophole in the question and lean formalization is flawed
700 papers 3down after 24hours because of sign error
llms still can't see straight
Replying to @mathillustrated
If it allows you to travel faster than light, if it cures cancer, if it gives you an unlimited source of energy, who cares whether some scientists say they understand it.
NGL bro, the idea that billionaires want neo-feudalism using AI is going from a psycho conspiracy theory to reality every day.
now they want you to believe unverified results saying maybe the human mind doesn't understand
spectre retweeted
ok bro...
the artcraft dude got into my discord server and copied photon. but honestly - I like your approach and I wish you the best. no need to hide tho. we all copy.
spectre retweeted
I don't think an unmanned demo of a hunk of metal with wheels flying in the air is all that impressive.
Jamie and Adam from Mythbusters did similar stunts like 20 years ago. Except theirs was built by a team of 10 people, in just few days, on a shoe string budget.
spectre retweeted
it is genuinely hilarious that the $20/mo plan for Google includes Opus 5.5, but that they're gating Gemini 4 😂
the 2.8k likes prove that the ai hype crowd are bots
spectre retweeted
BREAKING: OpenAI’s solution to Navier–Stokes does not match its Lean verification.
The most important article to read today is not one of OpenAI’s 700 AI-generated math papers.
It is this other paper, making a deep and worrying point:
A Lean-verified proof does not automatically validate the proof written in natural language, nor does it mean that the formal statement captures the intended theorem.
During translation, an AI can change an assumption, weaken a statement, or replace the argument entirely.
It can hallucinate another theorem.
Lean correctly verifies the result.
But the proved result may no longer be what the paper claims.
This is a general problem. Things get spicy when the authors examine OpenAI’s proposed Navier–Stokes solution.
They identify at least two mismatches between the written intermediate results and their Lean counterparts:
One estimate claims that four additional input derivatives suffice. The Lean version requires five: a weaker result.
A pressure-flux estimate is obtained through a different bound, and proved through a different argument.
It is not clear whether these mismatches invalidate the entire proof.
But they raise an important issue.
OpenAI is flooding us with claimed revolutionary breakthroughs. Yet nobody knows whether the proofs are correct or whether they prove what they claim to be proving.
Epistemia at scale.
*
Paper in the first reply
spectre retweeted
The benchmark I actually care about:
Can our parents live longer?
Can we cure Alzheimer's?
Can we kill common cancers?
Can we prevent kids dying from rare diseases?
Why so much effort to solve low impact math problems? If these unreleased models are so good, solve real problems
We’re releasing a broad range of new mathematical results produced by an internal frontier model.
We’ve been consulting with the independent Advisory Group on Mathematics and Artificial Intelligence at the Institute for Advanced Study, and we have drawn on their advice and public recommendations to inform how we release these results.
github.com/openai/math
WHPX on ARM64 is virtualization cosplay: no 16K pages, no interrupt controller, QMP can't even read guest RAM,
instead of doing this you could have improved the platform
Today during the @AMD's #IFA2026 keynote, @pavandavuluri introduced Project Zenith - A ready-to-code Windows experience on developer-class devices.
Debuting on AMD's Ryzen AI Halo, with more devices to come. blogs.windows.com/windowsdev…












































